Creating Loop per Company
# for(x in 0:2) { # Changed to 0:2 since you only have 3 conditions
# if(x == 0) { # Parentheses around condition and curly braces
# fill_color <- "lightblue"
# variable_name <- "Climate Count" # This should match your column name
# category <- "Climate"
# } else if(x == 1) { # 'else if' instead of 'elif'
# fill_color <- "orange"
# variable_name <- "Sustainable Count" # Match your column name
# category <- "Sustainable"
# } else if(x == 2) {
# fill_color <- "hotpink"
# variable_name <- "Environmental Count" # Match your column name
# category <- "Environmental"
# }
#
# all_years <- as.character(2002:2024)
#
# # Create plot
# print( # Need print() inside loops to display ggplot
# ggplot(apple_data, aes(x = factor(Year), y = .data[[variable_name]])) + # Dynamic column reference
# geom_bar(stat = "identity",
# fill = fill_color, # Use the dynamic color
# width = 0.6,
# alpha = 0.9,
# color = "white",
# linewidth = 0.3) +
# scale_x_discrete(limits = all_years, drop = FALSE) +
# scale_y_continuous(limits = c(0, 50), expand = c(0, 0)) +
# labs(title = paste("Occurrence of", category, "in Apple 10k Forms"), # Use paste() for string concatenation
# subtitle = "Annual Frequency (2002-2024)",
# x = NULL,
# y = "Count") +
# theme_minimal(base_size = 13) +
# theme(
# plot.title = element_text(hjust = 0.5, face = "bold", size = rel(1.2), margin = margin(b = 8)),
# plot.subtitle = element_text(hjust = 0.5, color = "gray40", margin = margin(b = 15)),
# axis.text.x = element_text(angle = 45, hjust = 1, color = "gray30"),
# axis.text.y = element_text(color = "gray30"),
# panel.grid.major.x = element_blank(),
# panel.grid.minor.y = element_blank(),
# panel.grid.major.y = element_line(color = "gray90", linewidth = 0.3),
# plot.margin = unit(c(1, 1, 1, 1), "cm")
# )
# )
# }
Iterating through 100?
library(readxl)
library(ggplot2)
## Warning: package 'ggplot2' was built under R version 4.3.3
# Get first 5 company names
sheet_names <- excel_sheets("C:/Users/alexi/Downloads/Processed EDGAR API Links.xlsx")[1:100]
for(company in sheet_names) {
# Read data (no changes to your original graph code)
company_data <- read_excel("C:/Users/alexi/Downloads/Processed EDGAR API Links.xlsx",
sheet = company)
# Print company header
cat("\n\n##", company, "\n\n")
# Your perfect graph code - now with headers for each plot type
for(x in 0:2) {
if(x == 0) {
fill_color <- "lightblue"
variable_name <- "Climate Count"
} else if(x == 1) {
fill_color <- "orange"
variable_name <- "Sustainable Count"
} else {
fill_color <- "hotpink"
variable_name <- "Environmental Count"
}
# Your exact plotting code
print(
ggplot(company_data, aes(x = factor(Year), y = .data[[variable_name]])) +
geom_bar(stat = "identity",
fill = fill_color,
width = 0.6,
alpha = 0.9,
color = "white",
linewidth = 0.3) +
scale_x_discrete(limits = as.character(2001:2024), drop = FALSE) +
scale_y_continuous(expand = c(0, 0)) +
labs(title = paste(variable_name, "in", company),
x = NULL,
y = "Count") +
theme_minimal() +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
)
}
}
##
##
## ## Apple
##
##
## ## Cencora
##
##
## ## Tesla
##
##
## ## Walmart
##
##
## ## Amazon
##
##
## ## Berkshire Hathaway
##
##
## ## CVS Health
##
##
## ## Exxon Mobil
##
##
## ## Alphabet
##
##
## ## McKesson
##
##
## ## Costco
##
##
## ## Microsoft
##
##
## ## Cardinal Health
##
##
## ## Chevron
##
##
## ## JP Morgan
##
##
## ## Toyota Motor
##
##
## ## Meta
##
##
## ## Morgan Stanley
##
##
## ## Citigroup
##
##
## ## Verizon Communications
##
##
## ## Comcast
##
##
## ## Johnson & Johnson
##
##
## ## American Express
##
##
## ## Procter and Gamble
##
##
## ## General Motors
##
##
## ## Broadcom
##
##
## ## Pepsi
## Warning: Removed 1 row containing missing values or values outside the scale range
## (`geom_bar()`).
## Warning: Removed 1 row containing missing values or values outside the scale range
## (`geom_bar()`).
## Warning: Removed 1 row containing missing values or values outside the scale range
## (`geom_bar()`).
##
##
## ## Home Depot
##
##
## ## Oracle
##
##
## ## Elevance Health
##
##
## ## ABBvie
##
##
## ## Cisco Systems
##
##
## ## Cigna Group
##
##
## ## Coca Cola
##
##
## ## IBM
##
##
## ## Caterpillar
##
##
## ## Intel
##
##
## ## John Deere
##
##
## ## ConocoPhillips
##
##
## ## Nvidia
##
##
## ## RTX
##
##
## ## US Bancorp
##
##
## ## Ford Motors
##
##
## ## Capital One
##
##
## ## Apollo Global Management
##
##
## ## Visa
##
##
## ## American International Group
##
##
## ## Charles Schwab
##
##
## ## Progressive
##
##
## ## PNC Financial Services
##
##
## ## Marathon Petroleum
##
##
## ## United Parcel Service
##
##
## ## NextEra Energy
##
##
## ## Walt Disney
##
##
## ## Phillips 66
##
##
## ## Metlife
##
##
## ## Salesforce
##
##
## ## Merck & Co.
##
##
## ## Abbott Laboratories
##
##
## ## FedEx
##
##
## ## Dell Technologies
##
##
## ## Lockheed Martin
##
##
## ## ELI LILY AND COMPANY
##
##
## ## KKR & Co. Inc
##
##
## ## Philip Morris International Inc
##
##
## ## Valero Energy
##
##
## ## Bank of New York Mellon Corp
##
##
## ## Prudential Financial
##
##
## ## Lowes
##
##
## ## Charter Communications
##
##
## ## Honeywell International
##
##
## ## Duke Energy
##
##
## ## Qualcomm
##
##
## ## HCA Healthcare
##
##
## ## Amgen
##
##
## ## Danaher
##
##
## ## Mondelez International
##
##
## ## Target
##
##
## ## Netflix
##
##
## ## Travelers
##
##
## ## Union Pacific
##
##
## ## Mcdonalds
##
##
## ## Centene
##
##
## ## Paypal
##
##
## ## Mastercard
##
##
## ## Delta Air Lines
##
##
## ## General Dynamics
##
##
## ## Nike
##
##
## ## Aflac
##
##
## ## Occidental Petroleum
##
##
## ## Fiserv
##
##
## ## SLB
##
##
## ## TJX Cos
##
##
## ## Automatic Data Processng
##
##
## ## Kraft Heinz Company
##
##
## ## EOG Resources
##
##
## ## Applied Materials
##
##
## ## Archer Daniels Midland
##
##
## ## Marsh McLennan
##
##
## ## Adient
